Vision Framework

Objective

Create a reprogrammable module in which a Raspberry Pi 3, protective case, power cable, light ring, and camera are self contained and execute a base program on startup. The base code of the module continuously reads the camera feed (subscribes to camera) and publishes corresponding data via the Pi's serial output (located on the Pi's GPIO connector). This data can then be fairly simply read by the RoboRIO. We hope that this will make implementing a vision subsystem a more simple proposition, allowing more teams to do so.

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Materials

• Clear Case
• Raspberry Pi 3
• Micro SD card
• Usb Keyboard
• Usb Mouse
• HDMI cable
• Monitor (that accepts HDMI input, or use an HDMI to VGA adapter)
• Ribbon Cable Camera
• Micro USB Cable
• Adafruit NeoPixel? Light Ring
• 3 individual male to female PWM wires
• 3 individual female to female PWM wires

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Raspberry Pi Setup

Raspbian Lite

Install ​Win32 Disk Imager
Install ​Raspian Lite onto MicroSD card via Win32 Disk Imager

Load Raspberry Pi 3 (rpi) with the newly imaged MicroSD

username: pi
password: raspberry

connect to wifi by adding the following to the /etc/network/interfaces file:

auto wlan0
iface wlan0 inet dhcp
  wpa-ssid "your-ssid"
  wpa-psk  "your-password"

reboot the pi:

sudo shutdown -r now

update with the following commands:

sudo apt-get update
sudo apt-get upgrade
sudo apt-get dist-upgrade
sudo apt-get clean

set localization configuration options:

sudo raspi-config

reboot:

sudo shutdown -r now

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X server

Install Xorg and Xinit:

sudo apt-get install --no-install-recommends xserver-xorg
sudo apt-get install --no-install-recommends xinit

Install the MATE GUI:

sudo apt-get install mate-desktop-environment-core

Install LightDM login manager:

sudo apt-get install lightdm

reboot:

sudo shutdown -r now

login to MATE
At the top left:
navigate to preferences -> hardware -> keyboard shortcuts to set Run a Terminal to Ctrl + Alt + T or the like

open a terminal
navigate to Edit -> Profile Preferences -> Colors to deselect Use colors from system theme
select Built-in schemas: White on black

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Development Tools

Java 8

Now that the terminal color scheme is not killing you, we are going to start off by installing java:

sudo apt-get install oracle-java8-jdk

test the java installation (output should include "1.8.0_65" and should not include "openjdk"):

java -version

Let's also set the JAVA_HOME variable to be exported on startup:

echo "export JAVA_HOME=/usr/lib/jvm/jdk-8-oracle-arm32-vfp-hflt" >> ~/.bashrc
source ~/.bashrc

Finally, let's install ANT:

sudo apt-get install ant

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Pi4J (Java-GPIO Interface)

Now we can install ​pi4j, a Java interface for the pi GPIO:

curl -s get.pi4j.com | sudo bash

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rpi_ws281x (NeoPixel? Control Library)

Then we can use the rpi_ws281x library for controlling the ​Adafruit NeoPixel lightring
But first, let's install some tools and dependencies:

sudo apt-get install build-essential python-dev git scons swig

Now we can install the rpi_ws281x library:

git clone https://github.com/jgarff/rpi_ws281x.git
cd rpi_ws281x
scons

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OpenCV

First of all, order some pizza or something because this is going to take about 3 hours (if you are lucky).

EDIT: we have tried with a heatsink as well. It doesn't work. You need to water cool your pi. Please skip to the WATER COOLING section.

Also, you need a heatsink for your processor before building OpenCV. If you see this overheating symbol, you will die. Straight up.

If you don't have a heatsink on hand, tape some pennies to the CPU like we did:

================WATER COOLING================

If this still doesn't work, it may be necessary to water cool your pi:

Make sure to change the ice cube at least once every half hour. Also, only single bag the ice cube.

Now we are going to install OpenCV and its dependencies.
We only install OpenCV for C++ and Java, not for Python (we ain't scrubs):

sudo apt-get install cmake git libgtk2.0-dev pkg-config libavcodec-dev libavformat-dev libswscale-dev
cd
git clone https://github.com/opencv/opencv.git
cd opencv
mkdir build
cd build
cmake ..
make -j $[$(nproc)+1]
sudo make install

This builds a single shared object file (libopencv_java320.so), a jar file (opencv-320.jar) and a ton of static libraries (*.a)
It copies the shared object file and the jar file to the install directory: /usr/local/share/OpenCV/java/...

NOTE: we could not get the java wrapper to work with ffmpeg enabled (we ran into a Segmentation fault with opencv libs 3.2.0, 3.3.0, and 3.3.1). We gave up and disabled it.

If you do not want to git clone the master opencv repository, download a zipped version: ​opencv-3.2.0.zip

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Java Projects with OpenCV

Enable VideoCapture?

First, to allow OpenCV VideoCapture? to access the ribbon cable camera, execute the following:

echo "sudo modprobe bcm2835-v4l2" >> ~/.bashrc
source ~/.bashrc

Compiling

javac -d <build_path> -classpath <external_jars> <source_path>/*.java

where:

• build_path = directory to store class files
• external_jars = string specifying individual jar dependencies (such as OpenCV and Pi4J) with delimiters as follows:
  • :/path_to_jars/jar1.jar:/path_to_jars/jar2.jar
• souce_path = directory containing all of your java files to be compiled

We recommend creating a libs folder in which you store all of your external jars such as the opencv-320.jar and all the Pi4J jars rather than having your libraries scattered all over your machine.

Running

sudo java -Djava.library.path=<opencv_install_path> -Dpi4j.debug -Dpi4j.linking=dynamic -classpath <external_jars> <Main_class>

where:

• external_jars = same string that you used in the Compilation step
• Main_class = name of the class file with main method
  • For example, where Vision.class is the class file, Main_class = Vision

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C++ Projects with OpenCV

NOTE: our performance doubled when we transitioned to C++ from Java

With C++, we can process (capture and segment) 640x480 frames at 66 fps and 1080x720 frames at 28 fps

With Java, we could only get about 30 fps with 640x480 frames

Let's install an IDE so we do not have to keep writing in vi/vim/nano:

sudo apt-get install codeblocks

We experienced a bug that constantly crashed CodeBlocks:
To prevent crashing, navigate to: Settings -> Editor -> Code completion -> Symbols browser and check Disable symbols browser
(the Code completion tab is on the west panel of the configure editor.)

Navigate to: File -> New -> Project -> Console Application And fill in the fields that come up.

If your Management tab is not visible, open it by selecting: View -> Manager
Also, if your Logs & others tab is not open already, select View -> Logs

Now right click your project in the Management tab and navigate to: Build options... -> Linker settings

Under the Link libraries panel, select Add and select all OpenCV shared object (.so) files located in /home/pi/opencv/build/lib/*.so
(You can [ctrl + left-click] multiple *.so] files to add them all at once)

Now let's navigate to: Search directories -> Linker
In the Linker tab, select Add and add the path to your opencv lib: /home/pi/opencv/build/lib

Tricks and Tips

Using OpenCV with the Raspberry Pi 3 ribbon cable camera is a little cumbersome because you cannot use many of the VideoCapture?.set(char*,int) functions.
Instead, we use system commands to set camera settings via the v4l2-ctl library.

For FRC retroreflective tape segmentation, use the following system commands to prevent auto adjustment features such as auto exposure, white balance, and exposure time:

• v4l2-ctl --set-ctrl=auto_exposure=1
• v4l2-ctl --set-ctrl=white_balance_auto_preset=0
• v4l2-ctl --set-ctrl=auto_exposure_bias=0
• v4l2-ctl --set-ctrl=exposure_time_absolute=100

Make your C++ program set these options by using the stdlib.h system(char*) command which simply takes a string command as input.
Alternatively you could add these options to your bashrc file like we did with the modprobe, but you may want to tweak these options or experiment with them, so putting them into your C++ program makes it a little easier to manipulate.